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All Journal Teknika TELKOMNIKA (Telecommunication Computing Electronics and Control) Primary: Jurnal Pendidikan Guru Sekolah Dasar Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Jurnal CoreIT Journal of Natural Science and Integration Seminar Nasional Teknologi Informasi Komunikasi dan Industri J I M P - Jurnal Informatika Merdeka Pasuruan Applied Information System and Management Jurnal Nasional Komputasi dan Teknologi Informasi JURIKOM (Jurnal Riset Komputer) JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Jurnal IDAMAN (Induk Pemberdayaan Masyarakat Pedesaan) Building of Informatics, Technology and Science Jutisi: Jurnal Ilmiah Teknik Informatika dan Sistem Informasi Zonasi: Jurnal Sistem Informasi INFORMASI (Jurnal Informatika dan Sistem Informasi) JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) Journal of Computer System and Informatics (JoSYC) Jurnal Sistem Komputer dan Informatika (JSON) TIN: TERAPAN INFORMATIKA NUSANTARA Jurnal Teknik Informatika (JUTIF) Jurnal Computer Science and Information Technology (CoSciTech) Jurnal Pendidikan dan Teknologi Indonesia Bulletin of Computer Science Research KLIK: Kajian Ilmiah Informatika dan Komputer Knowbase : International Journal of Knowledge in Database Malcom: Indonesian Journal of Machine Learning and Computer Science SATIN - Sains dan Teknologi Informasi
Pizaini Pizaini
Universitas Islam Negeri Sultan Syarif Kasim Riau
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Implementasi Treemap untuk Visualisasi Data Angka Kesakitan (Morbiditas) (Studi Kasus: Dinas Kesehatan Indragiri Hilir) Muhammad Ridha; Muhammad Affandes; Eka Pandu Cynthia; Pizaini Pizaini
Jurnal Nasional Komputasi dan Teknologi Informasi (JNKTI) Vol 5, No 2 (2022): April 2022
Publisher : Program Studi Teknik Komputer, Fakultas Teknik. Universitas Serambi Mekkah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32672/jnkti.v5i2.4147

Abstract

Dinas Kesehatan Indragiri Hilir merupakan instansi pemerintah yang memegang peranan penting dalam pengawasan dan pemantauan perkembangan kesehatan di Kabupaten Indragiri Hilir. Sebagai pihak yang bertanggung jawab dibidang kesehatan, Dinas Kesehatan memerlukan pendataan mengenai angka kesakitan (morbiditas) masyarakat Indragiri Hilir yang dikelompok berdasarkan penyakit, umur, jenis kelamin, kasus baru-lama yang ada disetiap UPT Puskesmas di Kabupaten Indragiri Hilir. Setiap bulannya, UPT Puskesmas di kecamatan melaporkan angka kesakitan (morbiditas) ke Dinas Kesehatan Indragiri Hilir untuk direkapitulasi. Namun laporan masih dalam bentuk format file excel dan tabel, sehingga data harus dilihat satu persatu dan memahami data membutuhkan waktu yang lama. Maka dibutuhkanlah sistem yang dapat memvisualisasikan data untuk memudahkan melihat data dan mengambil keputusan. Sistem ini dibangun menggunakan metode Treemap. Metode ini dapat memvisualisasikan data secara menyeluruh dan detail berdasarkan kategori data dengan jumlah data ratusan hingga ribuan yang ditampilkan dalam satu waktu. Berdasarkan hasil pengujian yang dilakukan menggunakan metode Black Box dan User Acceptance Test, sistem visualisasi menggunakan Treemap berhasil dibangun dan berjalan dengan baik dalam memvisualisasikan data angka kesakitan (morbiditas) di Indragiri Hilir dengan memperoleh hasil pengujian 95.10% untuk kategori sangat bagus menggunakan perhitungan skala Likert.
Algoritme Logistic Regression untuk Mendeteksi Ujaran Kebencian dan Bahasa Kasar Multilabel pada Twitter Berbahasa Indonesia Ayu Fransiska; Surya Agustian; Fitri Insani; Muhammad Fikry; Pizaini Pizaini
Jurnal Nasional Komputasi dan Teknologi Informasi (JNKTI) Vol 5, No 4 (2022): Agustus 2022
Publisher : Program Studi Teknik Komputer, Fakultas Teknik. Universitas Serambi Mekkah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32672/jnkti.v5i4.4524

Abstract

Abstrak - Ujaran kebencian semakin meningkat bersamaan dengan banyaknya pengguna media sosial. Twitter merupakan salah satu media sosial yang membantu penyeberan ujaran ujaran melalui fitur twit-nya yang dilakukan berulang-ulang. Penelitian ini dilakukan untuk mengklasifikasi apakah sebuah twit mengandung ujaran kebencian atau bahasa kasar, dan jika terdeteksi mengandung ujaran kebencian maka akan diukur tingkatannya. Dataset yang digunakan diambil dari twitter sebanyak 13.126 twit asli. Klasifikasi menggunakan Algoritma logistic Regression dan fitur teks word embedding. Dilakukan beberapa kali percobaan untuk mendapatkan model terbaik agar pengujian didapatkan secara optimal. Rata-rata akurasi yang dari ketiga kelas sebesar 75,59%, untuk kelas hate speech 75,86%,kelas abusive 80,05%, kelas level 70,86% dengan komposisi 90:10.Kata kunci: Klasifikasi, Logistic Regression, Ujaran Kebencian, Twitter. Abstract - Hate speech is increasing along with the number of social media users. Twitter is one of the social media that helps spread utterances through its repeated tweet features. This study was conducted to classify whether a tweet contains hate speech or abusive language, and if it is detected to contain hate speech, the level will be measured. The dataset used was taken from twitter as many as 13,126 original tweets. Classification using Logistic Regression Algorithm and word embedding text feature. Several experiments were carried out to get the best model so that the test was obtained optimally. The average accuracy of the three classes is 75.59%, for the hate speech class is 75.86%, the abusive class is 80.05%, the level class is 70.86% with a composition of 90:10.Keyword : Classification, Logistic Regression, Hate Speech, Twitter.
Pembentukan Kelompok Mahasiswa/Alumni Content Creator Gizi Seimbang Remaja untuk Mencegah Stunting dalam Aplikasi Stunting Calculator: Aplikasi Stunting Calculator Hayati, Aslis Wirda; Husnan, Husnan; Roziana, Roziana; Pizaini, Pizaini; Akhyar, Amany
Jurnal IDAMAN (Induk Pemberdayaan Masyarakat Pedesaan) Vol. 7 No. 2 (2023): Jurnal IDAMAN (Induk Pemberdayaan Masyarakat Pedesaan)
Publisher : Politeknik Kesehatan Kemenkes malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31290/j.idaman.v7i2.4037

Abstract

The problem of stunting adolescents in the world is currently 22.2% or about more than 150.8 million. In efforts to prevent and reduce the prevalence of stunting, it is necessary to provide education to adolescents regarding food consumption in accordance with the rules of balanced nutrition. Community service aims to foster new entrepreneurs based on science and technology, teaching skills by incorporating health sciences through digital training. The book "Balanced Nutrition for Adolescents: Prevent Stunting" has been digitally transformed and integrated into a stunting calculator application on smartphones, enabling adolescents to become content creators. Adolescents are expected to have knowledge about nutrition that will be inputted into the stunting calculator application, understand the preparation for data entry, and utilize the digitized book on a smartphone. The training took place from February to March 2023, comprising five Zoom meetings and one in-person session. There were 23 participants in the training, consisting of students and alumni from the Departments of Nutrition, Nursing, Midwifery, Medical Records, and Informatics Engineering in universities located in Riau and West Sumatra provinces. Each meeting involved assigning tasks to the participants, followed by assessment and discussion at the beginning of subsequent sessions. After the training, participants formed WhatsApp groups for communication and discussion to create content based on their respective interests. The training participants were awarded competence certificates as content creators
Analisis Pola Asosiasi Data Transaksi Penjualan Minuman Menggunakan Algoritma FP-Growth dan Eclat Najmi, Risna Lailatun; Irsyad, Muhammad; Insani, Fitri; Nazir, Alwis; ., Pizaini
Building of Informatics, Technology and Science (BITS) Vol 5 No 1 (2023): June 2023
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v5i1.3592

Abstract

Every day transaction activities between companies and consumers continue to be carried out. This makes transaction data more and more and accumulate. This transaction data can be processed into more useful information using technology. Data mining is a technology that can work on a collection of transaction data into information that can be taken by companies as decision makers. The association rule method is used as a method to see the relationship between items in a transaction data. To analyze transaction data, researchers used the FP-Growth and Eclat algorithms. There are three stages of association in this study which are distinguished from the confidence value. The results in the first stage have a minimum confidence value of 0.4, the FP-Growth algorithm produces 41 association pattern rules, while the Eclat algorithm produces 32 association pattern rules. Then in the second stage the minimum trust value is 0.5, the FP-Growth algorithm produces 40 association pattern rules, for the Eclat algorithm it produces 32 association pattern rules. In the third stage, the minimum trust value is 0.6, the FP-Growth algorithm generates 32 association pattern rules, while the Eclat algorithm generates 30 association pattern rules. The results of the association pattern rules show that the Eclat algorithm is more efficient in determining the association pattern rules than the Fp-Growth algorithm
Steganografi Gambar Menggunakan Metode Least Significant Bit Pada Citra Dengan Operasi XOR Adha, Martin; Yanto, Febi; Handayani, Lestari; Pizaini, Pizaini
Building of Informatics, Technology and Science (BITS) Vol 6 No 1 (2024): June 2024
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v6i1.5262

Abstract

One way to secure secret messages from other unauthorized parties is steganography. One of the most widely used methods in steganography is Least Significant Bit. This research uses images as cover images and secret images. The image is resized to a resolution of 512x512 pixels, The cover image uses an RGB channel image and the secret image also uses an RGB channel image. In this research, LSB will be combined with triple XOR so that it can increase the security of this message hiding method. Triple XOR is used to provide extra security to images that have a secret image (Stego Image) inserted. In this research, several tests were also carried out, including testing the Peak Signal to Noise Ratio (PSNR) and Mean Square Error (MSE), for robustness testing it was also carried out by making modifications to the stego image such as resizing, compressing, and adding and reducing contrast. The results of this research's PSNR testing are very good, namely approximately 49 dB and lower MSE. With the PSNR and MSE results, it can be proven that the LSB method has a good level of imperceptibility. In experiments on image resistance to modification, several experimental results show that secret image extraction in the stego image failed to be extracted, and from several experiments such as adding and reducing contrast, image rotation and lossless compression, the image inserted in the stego image was successfully extracted.
Pencarian adverse event yang timbul akibat penggunaan obat dexamethasone menggunakan algoritma apriori Nuradha Liza Utami; Alwis Nazir; Pizaini; Elvia Budianita; Fitri Insani
Computer Science and Information Technology Vol 5 No 1 (2024): Jurnal Computer Science and Information Technology (CoSciTech)
Publisher : Universitas Muhammadiyah Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Inflammation is the body's response to infection, irritation, or injury characterized by redness, increased temperature, swelling, and pain. Dexamethasone is one of the drugs from the corticosteroid group that is commonly used, dexamethasone has a wide indication in medicine is often considered a drug that can save lives, causing many people to then buy dexamethasone drugs without medical indications and prescriptions assuming dexamethasone drugs can treat various diseases. The use of dexamethasone can result in side effects including decreased immunity, diabetes, hypertension, moon face, osteoporosis, and cataracts. In addition to frequent side effects, adverse events may also occur. This study aims to find the relationship of adverse events that arise as a result of using dexamethasone drugs, by applying the data mining technique of association rule method with apriori algorithm. The dataset used in the research is sourced from the FDA Adverse event Reporting System (FAERS) database which is managed using the KDD stages which include data selection, cleaning, transformation, and data mining. the results of the research are implemented into the apriori algorithm data mining system and tested using the lift ratio value. The rules generated in this study have a lift ratio value of more than 1, which means that the rules generated are valid and show the benefits of these rules.
Penerapan Teknologi LangChain pada Question Answering System Fikih Empat Madzhab: Application of Langchain Technology to the Fiqh Question Answering System of Four Madhhab Rahayu, Suci; Harahap, Nazruddin Safaat; Agustian, Surya; Pizaini, Pizaini
MALCOM: Indonesian Journal of Machine Learning and Computer Science Vol. 4 No. 3 (2024): MALCOM July 2024
Publisher : Institut Riset dan Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57152/malcom.v4i3.1397

Abstract

Fikih sebagai ilmu yang luas, terkadang menimbulkan beragam persoalan dan perbedaan pandangan antara madzhab-madzhabnya. Tujuan pandangan ulama tentang isu-isu fikih adalah untuk memperkaya opsi pemahaman, bukan menyebabkan perpecahan. Keberadaan mazhab penting bagi umat Islam awam dalam memahami hukum Islam, karena membantu dalam menafsirkan Al-Qur'an dan Hadits untuk masalah sehari-hari. Pengiriman informasi saat ini dapat dilakukan dengan cepat dan mudah, salah satunya melalui aplikasi tanya jawab atau Question Answering System (QAS) terkait materi yang ingin diketahui oleh pengguna. Sehingga pada penelitian ini bertujuan membuat sebuah QAS berbasis web tentang fikih empat madzhab menggunakan teknologi LangChain dan Large Language Model (LLM). LangChain dan model LLM mampu memberikan jawaban atas pertanyaan terkait file Portable Document Format (PDF). QAS dilatih menggunakan kumpulan data berupa file PDF serta memanfaatkan model LLM untuk menghasilkan respons teks yang relevan terhadap pertanyaan yang diajukan oleh pengguna. Sistem yang telah dikembangkan berhasil memberikan respons kepada pengguna dengan pengujian menggunakan BERTScore yang mendapatkan nilai rata-rata dari precision sebesar 80%, recall sebesar 81%, dan f-1 score sebesar 81%. Sedangkan ROUGEScore mendapatkan nilai rata-rata dari ROUGE-1 sebesar 56%, 58%, dan 56%, ROUGE-2 sebesar 33%, 33%, 33%, dan ROUGE-L sebesar 43%, 44%, dan 43%.
Analisis Performa Jaringan Local Area Network Dengan Menggunakan Metode Quality Of Service Arvansyah, M Afdhol; Iwan Iskandar; Teddie Darmizal; Novriyanto, Novriyanto; Pizaini, Pizaini
KLIK: Kajian Ilmiah Informatika dan Komputer Vol. 4 No. 6 (2024): Juni 2024
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/klik.v4i6.1905

Abstract

The LAN network center of RSUD Arifin Achmad Pekanbaru is located in the EDP (Electrical Data Processing) building, from where the network is distributed to other buildings within RSUD Arifin Achmad Pekanbaru for data transfer. A common issue that arises is delays in sending and receiving data from computer users in other buildings, causing disruptions in the data reception process. To address this problem, a network performance analysis is necessary to assess the quality of both internet and intranet connections within the RSUD Arifin Achmad Pekanbaru LAN. Therefore, a research study was conducted to measure network performance using the Quality of Service (QoS) method. The objective of this study was to analyze and evaluate the quality of internet and intranet performance in the RSUD Arifin Achmad Pekanbaru LAN. The research findings for internet performance indicate that live streaming on YouTube (720p), downloading a 250MB file, uploading a 250MB file, and accessing national and international websites all fall into the “Excellent” category. Based on the TIPHON standard, the LAN internet network at RSUD Arifin Achmad Pekanbaru is considered very good. Regarding intranet performance, the average throughput is 27,835.666Kbps, with zero packet loss, placing it in the “Excellent” category. The average delay is 374.614ms, categorized as “Moderate,” and the average jitter is 11.46066937ms, categorized as “Good” according to the TIPHON standard
Intrusion Detection System (IDS) Pada Snort Dengan Bot Telegram Sebagai Sistem Notifikasi Terhadap Serangan Syn Flood dan Ping Of Death Zuriati Ardila Safitri; Elin Haerani; Rometdo Muzawi; Muhammad Affandes; Pizaini
SATIN - Sains dan Teknologi Informasi Vol 10 No 1 (2024): SATIN - Sains dan Teknologi Informasi
Publisher : STMIK Amik Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33372/stn.v10i1.1138

Abstract

Keamanan jaringan menjadi prioritas penting dalam era digital. Penelitian ini mengembangkan sistem Intrusion Detection System (IDS) berbasis Snort yang terintegrasi dengan bot Telegram untuk notifikasi real-time dan menggunakan kecerdasan buatan (AI) untuk mendeteksi serta mengelompokkan jenis serangan Syn Flood dan Ping of Death. Snort dikonfigurasi dengan aturan khusus untuk mendeteksi kedua jenis serangan ini. Bot Telegram digunakan untuk mengirimkan notifikasi langsung kepada administrator jaringan saat serangan terdeteksi. Hasil penelitian menunjukkan bahwa sistem ini mampu mendeteksi serangan dengan cepat, memberikan notifikasi real-time, dan mengelompokkan jenis serangan dengan akurasi tinggi. Integrasi ini meningkatkan efektivitas deteksi dan respons terhadap serangan jaringan, menawarkan solusi yang lebih aman dan efisien bagi organisasi.
Klasifikasi Sentimen pada Dataset Terbatas Menggunakan Random Forest dan Word2Vec Fitri, Dina Deswara; Agustian, Surya; Pizaini, Pizaini; Sanjaya, Suwanto
Journal of Computer System and Informatics (JoSYC) Vol 6 No 1 (2024): November 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josyc.v6i1.6246

Abstract

Sentiment measurement of public opinion on social media is essential for understanding societal views on various issues, including public figures and political events. This research explores the effectiveness of the Random Forest algorithm with Word2Vec-based word representation for sentiment classification on a limited dataset. The case study involves tweets regarding Kaesang Pangarep as the Chairman of PSI, supplemented by external data related to Covid-19 and general topics. The dataset was processed using cleaning techniques, case folding, stopword removal, stemming, and tokenization. Words in the dataset were represented using the Word2Vec model with a Continuous Bag of Words (CBOW) architecture and a vector dimension of 500. Random Forest was employed to classify sentiment into positive, negative, or neutral categories. In the initial phase, the model was trained using 300 samples per label; however, the results showed unsatisfactory performance with an F1-Score of 49.00% and an accuracy of 50.00%. To improve performance, the dataset was expanded by adding 900 samples from Kaesang and 1,080 samples from external topics. The final results indicated an improvement with an F1-Score of 49.89%, an accuracy of 58.29%, precision of 49.16%, and recall of 56.47%. This research confirms that the use of Random Forest with word representation from Word2Vec can enhance sentiment classification performance, even with a limited dataset, and contributes to the development of sentiment analysis techniques in the field of machine learning.
Co-Authors Abdillah, Rahmad Adha, Martin Aditya Dyan Ramadhan Afdhalel Vickro Agung Teguh Wibowo Almais Ahmad Fauzan Akhyar, Amany Albis Ya Albi Alwis Nazir Alwis Nazir Andrian Wahyu Arvansyah, M Afdhol Aslis Wirda Hayati Ayu Fransiska Bebi Oktaviani Che Hussin, Ab Razak citra ainul mardhia putri Deny Dewana Hastanto Dhymas Julyan Riyanto Eka Pandu Cynthia Elin Haerani Elvia Budianita Fadhilah Syafria Fahmi Kasri Fajar Febriyadi Fakhrezi, Muhammad Dzaki Faris Apriliano Eka Fardianto Faris Fauzan Ray T Febi Yanto Fitra Kurnia Fitri Insani Fitri Insani Fitri Insani Fitri, Dina Deswara Gusti, Siska Kurnia Haikal Zikri Hasibuan, Ilham Habibi Heru Sukoco Husnan Husnan Ibrahim Armadian Pujakesuma Iwan Iskandar Iwan Iskandar Iwan Iskandar Iwan Iskandar Iwan Jasril Jasril Jesi Alexander Alim Jesi Alexander Alim Kana Saputra S Khonofi, Khoidir Lestari Handayani Lola Oktavia m azwan M Wandi Dwi Wirawan M. Saski Mandiro, Mulia Anton Muhammad Affandes Muhammad Affandes Muhammad Fauzan Muhammad Fikry Muhammad Irsyad Muhammad Irsyad Muhammad Ridha Mulia Anton Mandiro Musa Thahir Muslimin, Al’hadiid Najmi, Risna Lailatun Nanda Sepriadi Nazir, Alwis Nazruddin Safaat H Neni Hermita Novi Yanti Novialdi T Novri Rahman Novriyanto Novriyanto Nur Iza Nuradha Liza Utami Okfalisa Okfalisa Okfalisa Okfalisa Putri, Adilah Atikah Rahmad Abdillah Rahmad Kurniawan Reski Mai Candra Reski Mai Chandra Rometdo Muzawi, Rometdo Roziana Roziana, Roziana Saktioto Saktioto Suci Rahayu Sugi Guritman Sukma Evadini Surya Agustian Suwanto Sanjaya Syarifuddin Syarifuddin Tarmizi, Veci Cahyono Teddie Darmizal Thahir, Musa Tommy Tanu Wijaya Umar Syarif Vebrianto, Rian Wenny Tarisa Oktaviany Wirdiani, Putri Syakira Yelfi Vitriani Yusra Yusra, Yusra Zuriati Ardila Safitri